Biology subjects

Porter, L.

Publications and source records attributed to Porter, L..

At least 19 recordsLinked to original sources

bioRxiv2026

Effects of ERK1/2 Signaling on Cell Cycle Regulation by the Tuberin-Cyclin B1 Complex

How cells balance growth (cell size) and division (cell number) requires a complex interplay between response to external signals including growth factors, nutrient availability and metabolic cues, along with regulation of the cell cycle. The protein Tuberin (gene TSC2) is a critical regulator of these decisions. In a complex with the protein Hamartin, Tuberin functions as a negative regulator of the Target of Rapamycin (mTOR) pathway, preventing excessive growth under unfavorable conditions. However, how this growth pathway connects to decisions to progress through the G2 phase of the cell cycle and permit cell division is still unclear. In this study, we show that post-translational modification of Tuberin by the Extracellular Signal-Regulated Kinase (ERK) pathway abrogates binding between Tuberin and the mitotic cyclin, Cyclin B1. This causes an increase in mitotic cells, due to an unregulated G2/M transition, increasing the proliferation rate. Our work shows a novel role of Tuberin in cell cycle regulation by growth and mitogenic factors independent of mTOR regulation.

cell biology↗

bioRxiv2026

A dramatic protein fold switch powers a bactericidal nanomachine

Fold switching, where a protein region interconverts between entirely distinct three-dimensional structures, is emerging as vital for certain protein functions. Here, we report a remarkable example in the F7 pyocin, a phage tail-like bactericidal nanomachine. Cryogenic electron microscopy and tomography reveal that a 163-residue segment of the central tail fiber undergoes a dramatic transition--from a trimeric -helical coiled-coil to a triangular {beta}-prism--upon binding to the bacterial cell surface. This massive fold switch remodels the tail tip, ejects the internal tape measure protein, and drives membrane puncture. Site-directed mutations that selectively destabilize the {beta}-prism conformation completely abolish bactericidal activity without impairing particle assembly, implying that the energy released during this transition powers penetration. AlphaFold-based analyses further predict similar large-scale coiled-coil to {beta}-prism switches in diverse non-contractile phage tails. This discovery reveals a sophisticated, ATP-independent strategy for microbial warfare and opens exciting possibilities for engineering next-generation bacteriocins to combat multidrug-resistant pathogens.

microbiology↗

bioRxiv2026

Explaining how mutations affect AlphaFold predictions

Proteins can adopt many distinct conformations, yet the sequence determinants governing which structural states are accessible remain poorly understood. Using fold-switching proteins and AlphaFold as an analytical lens, we identify an organizational principle in which access to alternative structural states-and in some cases the folded state-is governed by surprisingly few amino acids, termed gating residues. Gating generalizes to single-fold proteins, indicating that conformational accessibility is often hierarchically organized around a small number of disproportionately influential residues. AlphaFold has implicitly learned this principle but amplifies and sometimes misapplies it, concentrating conformational control onto too few or incorrect residues. Guided by this principle, targeted MSA editing recovered a conformation AlphaFold confidently mispredicted, suggesting a path toward more accurate prediction of alternative conformations and mutational effects.

bioinformatics↗

bioRxiv2025

Detection of environmental DNA of the Indo-Pacific humpback dolphins in Hong Kong waters using quantitative PCR

Environmental DNA (eDNA) analysis is a promising method to enhance the sensitivity and efficiency of biodiversity monitoring. In Hong Kong, the Indo-Pacific humpback dolphin (Sousa chinensis) is an iconic marine mammal inhabiting shallow coastal regions, playing a vital role in the local biodiversity. However, their population is declining, highlighting the need for effective monitoring methods for S. chinensis. In this study, we developed a species-specific qPCR assay for detecting S. chinensis eDNA. We designed primers and a probe targeting the Cytb region of mitochondrial DNA. Specificity tests and evaluations of the limit of detection and quantification demonstrated that the primers and probe possess sufficient specificity and sensitivity to detect S. chinensis eDNA. Our qPCR method was further validated by detecting S. chinensis eDNA in water samples collected from areas where S. chinensis individuals were sighted. Analysis of 56 coastal water samples collected over two seasons revealed that S. chinensis utilizes the western and southern Lantau regions of Hong Kong waters. With further enhancements to the eDNA-based survey method, including larger water volumes, broader spatial coverage, and targeting other cetaceans and fish, our framework will aid in the conservation of S. chinensis in Hong Kong waters.

ecology↗

bioRxiv2025

Fiber-based hydrogels for designing viscoelastic responses in particle-based biomaterials that support embedded 3D printing

Viscoelastic biomaterials that exhibit biomimetic responses to applied stresses are important in studying physiology and designing biomaterial scaffolds. Particle-based hydrogels offer potential for engineering viscoelasticity through design of both the component microparticles and their processing into bulk particle-based materials. When particles are not crosslinked to one another, particle movements in response to strain can potentially relieve applied stresses and facilitate the materials use in dynamic processes like bioprinting. In particle-based hydrogels based on spherical hydrogel microparticles (HMPs), particle movement is restricted by contacts with immediately adjacent HMPs. In comparison, fiber-based hydrogel systems leverage high-aspect ratio microfiber components with long-range interactions. Here, microfibers with aspect ratios of [~]15:1 length:diameter are used to form particle-based hydrogels to compare how interparticle interactions at increased length scales alter properties compared to particle-based hydrogels based on spherical HMPs. Like particle-based hydrogels formed from spherical HMPs, those formed from fiber HMPs exhibit viscoelasticity, with shear-thinning and self-healing behaviors. But, fiber-based materials allow enhanced control over bulk stress relaxation times (T1/2 [~] 1-100+ s) across a range of applied strains ({sigma} [~] 2.5-50%) in a packing density-dependent fashion. Fiber-based systems relaxed stresses continually and to a greater degree at low strains in comparison to HMP systems. Dynamic interfiber interactions in fiber-based hydrogels also supported embedded printing where perfusable channels can be printed into fiber-based hydrogels stabilized by physical interfiber interactions. Taken together, fiber-based hydrogels offer opportunities for designing complexity into biomaterial scaffolds, including allowing control over viscoelastic properties through hydrogel design and control over heterogeneous 3D structures through embedded printing.

bioengineering↗

bioRxiv2025

μCeta: a set of cetacean-specific primers for environmental DNA metabarcoding with minimal amplification of non-target vertebrates

Biodiversity monitoring is crucial for understanding ecosystem dynamics and species distributions, particularly in the context of anthropogenic impacts and climate change. Cetaceans, as key indicator species of marine ecosystems, face increasing threats from human activities, highlighting the need for effective, non-invasive monitoring methods. In the present study, we developed novel Cetacea-specific primer sets to enhance the detection efficiency of cetacean species through environmental DNA (eDNA) metabarcoding, while minimizing the amplification of non-target vertebrates, such as fish and humans. We retrieved mitochondrial genomes of 71 cetacean species from a public database and designed 20 candidate primer sets, which were assessed in silico for their specificity and capacity to differentiate cetacean sequences. Four primer sets with the best in silico performance were selected for empirical validation using DNA from tissue samples and eDNA from seawater collected from aquarium pools and Hong Kong coastal waters. All four primer sets effectively amplified cetacean DNA from tissue samples. However, in the aquarium pool tests, three primer sets failed to accurately identify one or more cetacean species due to a lack of interspecific variation within the amplified region. From these, we selected one primer set targeting a 267 bp region of the mitochondrial 12S rRNA gene, named {micro}Ceta, and applied it to water samples collected from Hong Kong coastal waters, where the iconic Indo-Pacific humpback dolphin (Sousa chinensis) was observed. {micro}Ceta successfully detected S. chinensis eDNA while avoiding amplification of non-target species such as fish or humans. Our results demonstrate that {micro}Ceta is a reliable tool for cetacean eDNA detection in Hong Kong waters, contributing to cetacean conservation and enhancing our understanding of marine biodiversity.

ecology↗

bioRxiv2024

AlphaFold2's training set powers its predictions of fold-switched conformations

AlphaFold2 (AF2), a deep-learning based model that predicts protein structures from their amino acid sequences, has recently been used to predict multiple protein conformations. In some cases, AF2 has successfully predicted both dominant and alternative conformations of fold-switching proteins, which remodel their secondary and tertiary structures in response to cellular stimuli. Whether AF2 has learned enough protein folding principles to reliably predict alternative conformations outside of its training set is unclear. Here, we address this question by assessing whether CFold-an implementation of the AF2 network trained on a more limited subset of experimentally determined protein structures- predicts alternative conformations of eight fold switchers from six protein families. Previous work suggests that AF2 predicted these alternative conformations by memorizing them during training. Unlike AF2, CFolds training set contains only one of these alternative conformations. Despite sampling 1300-4400 structures/protein with various sequence sampling techniques, CFold predicted only one alternative structure outside of its training set accurately and with high confidence while also generating experimentally inconsistent structures with higher confidence. Though these results indicate that AF2s current success in predicting alternative conformations of fold switchers stems largely from its training data, results from a sequence pruning technique suggest developments that could lead to a more reliable generative model in the future.

bioinformatics↗

bioRxiv2024

Modelling Glioma Stem Cell-mediated Tumorigenesis Using Zebrafish PDX Systems

Glioblastoma is an aggressive brain tumour associated with high post-therapy recurrence and very poor survival rates. One of the factors contributing to the aggressive nature of this disease is the level of heterogeneity seen at the phenotypic and genetic level. Glioma Stem Cells (GSCs) are stem-like cells within the tumour with the ability to self-renew and give rise to different types of cells within the tumour, hence giving rise to the heterogeneity found in glioblastoma. GSCs are often implicated in the resistance of glioma to standard of care radiation and chemotherapy. The physical niche within a tumour mass supports stemness and aggressive characteristics of GSCs, hence, experimental systems providing a relevant tumour microenvironment are critical for adequate assessment of molecular mechanisms regulating GSC populations. Although, mouse models are a staple of an in vivo experimental design, they are neither time-nor cost-efficient. Danio rerio (zebrafish) patient-derived xenografts (PDXs) overcome several of the obstacles of the mammalian systems. Zebrafish constitute a high throughput, easily reproducible experimental platform allowing for life relevant investigation into the aggressiveness of GSC populations. This chapter describes methods required for generation of zebrafish PDXs to study aspects of GSC-mediated tumorigenesis and interactions with the tumour microenvironment. Consistency between labs for these experiments is required to move the discovery of effective treatments for glioblastoma moving forward.

cancer biology↗

bioRxiv2024

Profiling Glioma Stem Cell Dynamics via 3D-based Cell Cycle Reporter Assays

Successful containment of unwanted cell cycle progression in tumours such as glioblastoma (GBM) requires targeted therapeutic approaches which rely on understanding cell cycle dynamics in response to microenvironmental stimuli. Glioma Stem Cells (GSCs) can drive tumour initiation, recurrence, therapy resistance, and are often attributed to the heterogeneity and plasticity of GBM. In vitro models using patient-derived GSCs provide a life relevant tool for exploration of complex molecular mechanisms underlying the aggressive characteristics of GBM. Introduction of 3D tissue culture systems permits the study of spatial complexity of the tumour mass and enables control over diverse conditions within the surrounding microenvironment. This chapter demonstrates detailed methods to study spatio-temporal changes to the cell cycle dynamics using available fluorescent cell cycle reporter systems in combination with bioinformatics-based signal intensity and localization analysis. We present a successful approach that investigates the 3D cell cycle dynamics of GSC populations. This approach utilizes GBM neurosphere and organoid cultures, which are assessed over time and under therapeutic pressure. These models can be further explored, manipulated, and customized to serve specific experimental designs.

cancer biology↗

bioRxiv2024

Sequence clustering confounds AlphaFold2

Though typically associated with a single folded state, some globular proteins remodel their secondary and/or tertiary structures in response to cellular stimuli. AlphaFold21 (AF2) readily generates one dominant protein structure for these fold-switching (a.k.a. metamorphic) proteins2, but it often fails to predict their alternative experimentally observed structures3,4. Wayment-Steele, et al. steered AF2 to predict alternative structures of a few metamorphic proteins using a method they call AF-cluster5. However, their Paper lacks some essential controls needed to assess AF-clusters reliability. We find that these controls show AF-cluster to be a poor predictor of metamorphic proteins. First, closer examination of the Papers results reveals that random sequence sampling outperforms sequence clustering, challenging the claim that AF-cluster works by "deconvolving conflicting sets of couplings." Further, we observe that AF-cluster mistakes some single-folding KaiB homologs for fold switchers, a critical flaw bound to mislead users. Finally, proper error analysis reveals that AF-cluster predicts many correct structures with low confidence and some experimentally unobserved conformations with confidences similar to experimentally observed ones. For these reasons, we suggest using ColabFold6-based random sequence sampling7-augmented by other predictive approaches-as a more accurate and less computationally intense alternative to AF-cluster.

bioinformatics↗

bioRxiv2023

Atypical Cell Cycle Regulation over Neural Stem Cell Expansion

Populations of adult neural stem cells (NSCs) that reside in the mammalian brain aid in neurogenesis throughout life and can be identified by a type VI intermediate filament protein, Nestin. Cell cycle regulation plays an important role in maintaining a balance between self-renewal and differentiation and determining the fate of NSCs. Data from our group and others support that the atypical cyclin-like protein Spy1 (also called RingoA; gene SPDYA) plays a critical role in activating NSCs from a quiescent state. Elevated levels of Spy1 are found in aggressive human brain cancers, including glioblastoma. Using a conditional mouse model, we demonstrate that driving the expression of Spy1, in the Nestin-enriched NSC population of the brain, increases stemness characteristics, decreases differentiation, and increases susceptibility to oncogenic transformation. This study contributes to better understanding of intricate cell cycle mechanisms which lead to deviation from the homeostatic state, promoting aberrant changes in adult NSCs.

molecular biology↗

bioRxiv2023

AlphaFold2 has more to learn about protein energy landscapes

Recent work suggests that AlphaFold2 (AF2)-a deep learning-based model that can accurately infer protein structure from sequence-may discern important features of folded protein energy landscapes, defined by the diversity and frequency of different conformations in the folded state. Here, we test the limits of its predictive power on fold-switching proteins, which assume two structures with regions of distinct secondary and/or tertiary structure. Using several implementations of AF2, including two published enhanced sampling approaches, we generated >280,000 models of 93 fold-switching proteins whose experimentally determined conformations were likely in AF2s training set. Combining all models, AF2 predicted fold switching with a modest success rate of [~]25%, indicating that it does not readily sample both experimentally characterized conformations of most fold switchers. Further, AF2s confidence metrics selected against models consistent with experimentally determined fold-switching conformations in favor of inconsistent models. Accordingly, these confidence metrics-though suggested to evaluate protein energetics reliably-did not discriminate between low and high energy states of fold-switching proteins. We then evaluated AF2s performance on seven fold-switching proteins outside of its training set, generating >159,000 models in total. Fold switching was accurately predicted in one of seven targets with moderate confidence. Further, AF2 demonstrated no ability to predict alternative conformations of two newly discovered targets without homologs in the set of 93 fold switchers. These results indicate that AF2 has more to learn about the underlying energetics of protein ensembles and highlight the need for further developments of methods that readily predict multiple protein conformations.

bioinformatics↗

bioRxiv2023

Evolutionary selection of proteins with two folds

Although most globular proteins fold into a single stable structure1, an increasing number have been shown to remodel their secondary and tertiary structures in response to cellular stimuli2. State-of-the-art algorithms3-5 predict that these fold-switching proteins assume only one stable structure6,7, missing their functionally critical alternative folds. Why these algorithms predict a single fold is unclear, but all of them infer protein structure from coevolved amino acid pairs. Here, we hypothesize that coevolutionary signatures are being missed. Suspecting that over-represented single-fold sequences may be masking these signatures, we developed an approach to search both highly diverse protein superfamilies-composed of single-fold and fold-switching variants-and protein subfamilies with more fold-switching variants. This approach successfully revealed coevolution of amino acid pairs uniquely corresponding to both conformations of 56/58 fold-switching proteins from distinct families. Then, using a set of coevolved amino acid pairs predicted by our approach, we successfully biased AlphaFold25 to predict two experimentally consistent conformations of a candidate protein with unsolved structure. The discovery of widespread dual-fold coevolution indicates that fold-switching sequences have been preserved by natural selection, implying that their functionalities provide evolutionary advantage and paving the way for predictions of diverse protein structures from single sequences.

bioinformatics↗

bioRxiv2022

Identification of a covert evolutionary pathway between two protein folds

Although homologous protein sequences are expected to adopt similar structures, some amino acid substitutions can interconvert -helices and {beta}-sheets. Such fold switching may have occurred over evolutionary history, but supporting evidence has been limited by the: (1) abundance and diversity of sequenced genes, (2) quantity of experimentally determined protein structures, and (3) assumptions underlying the statistical methods used to infer homology. Here, we overcame these barriers by applying multiple statistical methods to a family of ~600,000 bacterial response regulator proteins. We found that their homologous DNA-binding subunits assume divergent structures: helix-turn-helix versus -helix+{beta}-sheet (winged helix). Phylogenetic analyses, ancestral sequence reconstruction, and AlphaFold2 models indicated that amino acid substitutions facilitated a switch from helix-turn-helix into winged helix. This structural transformation likely expanded DNA-binding specificity. Our approach uncovers an evolutionary pathway between two protein folds and provides methodology to identify secondary structure switching in other protein families.

bioinformatics↗

bioRxiv2021

Dissecting the Roles of the Tuberin Protein in the Subcellular Localization of the G2/M Cyclin, Cyclin B1

Tuberin is a major component of the protein regulatory complex known as the Tuberous Sclerosis Complex and plays a crucial role in cell cycle progression and protein synthesis. Mutations in the Tuberin gene, TSC2, lead to the formation of benign tumors in many organ systems and causes the Tuberous Sclerosis Complex disorder. Genotypes ranging from point mutations to large deletions in the TSC2 gene have been clinically characterized with a wide range of phenotypes from skin tumors to large brain tumors. Our current work investigates the molecular mechanisms behind Tuberin and its ability to regulate the cell cycle through its binding to the G2/M cyclin, Cyclin B1. After creating an early stop codon in a critical region of the Tuberin, our results show the in vitro phenotype that occurs from a truncated Tuberin protein. Herein we demonstrate that this clinically relevant truncated form of Tuberin promotes an increased nuclear accumulation of Cyclin B1 and a subsequent increase in cell proliferation supporting the phenotypic data seen in the clinic with Tuberous Sclerosis Complex patients showing deletions within the TSC2 gene. This data provides an insight into some of the functional and molecular consequences of truncated proteins that are seen in clinical patients.

cell biology↗

bioRxiv2021

Cigarette smoke preferentially induces full length ACE2 exposure in primary human airway cells but does not alter susceptibility to SARS-CoV-2 infection

Cigarette smoking has multiple serious negative health consequences. However, the epidemiological relationship between cigarette smoking and SARS-CoV-2 infection is controversial; and the interaction between cigarette smoking, airway expression of the ACE2 receptor and the susceptibility of airway cells to infection is unclear. We exposed differentiated air-liquid interface cultures derived from primary human airway stem cells to cigarette smoke extract (CSE) and infected them with SARS-CoV-2. We found that CSE increased expression of full-length ACE2 (flACE2) but did not alter the expression of a Type I-interferon sensitive truncated ACE2 that lacks the capacity to bind SARS-CoV-2 or a panel of interferon-sensitive genes. Importantly, exposure to CSE did not increase viral infectivity despite the increase in flACE2. Our data are consistent with epidemiological data suggesting current smokers are not at excess risk of SARS-CoV-2 infection. This does not detract from public health messaging emphasising the excess risk of severe COVID-19 associated with smoking-related cardiopulmonary disease.

microbiology↗

bioRxiv2021

Pervasive fold switching in a ubiquitous protein superfamily

Hundreds of millions of structured proteins sustain life through chemical interactions and catalytic reactions1. Though dynamic, these proteins are assumed to be built upon fixed scaffolds of secondary structure, -helices and {beta}-sheets. Experimentally determined structures of over >58,000 non-redundant proteins support this assumption, though it has recently been challenged by [~]100 fold-switching proteins2. These "metamorphic3" proteins, though ostensibly rare, raise the question of how many uncharacterized proteins have shapeshifting-rather than fixed-secondary structures. To address this question, we developed a comparative sequence-based approach that predicts fold-switching proteins from differences in secondary structure propensity. We applied this approach to the universally conserved NusG transcription factor family of [~]15,000 proteins, one of which has a 50-residue regulatory subunit experimentally shown to switch between -helical and {beta}-sheet folds4. Our approach predicted that 25% of the sequences in this family undergo similar -helix {rightleftharpoons} {beta}-sheet transitions, a frequency two orders of magnitude larger than previously observed. Our predictions evade state-of-the-art computational methods but were confirmed experimentally by circular dichroism and nuclear magnetic resonance spectroscopy for all 10 assiduously chosen dissimilar variants. These results suggest that fold switching is a pervasive mechanism of transcriptional regulation in all kingdoms of life and imply that numerous uncharacterized proteins may also switch folds.

bioinformatics↗

bioRxiv2021

A sequence-based method for predicting extant fold switchers that undergo α-helix <-> β-strand transitions

Extant fold-switching proteins remodel their secondary structures and change their functions in response to cellular stimuli, regulating biological processes and affecting human health. In spite of their biological importance, these proteins remain understudied. Few representative examples of fold switchers are available in the Protein Data Bank, and they are difficult to predict. In fact, all 96 experimentally validated examples of extant fold switchers were stumbled upon by chance. Thus, predictive methods are needed to expedite the process of discovering and characterizing more of these shapeshifting proteins. Previous approaches require a solved structure or all-atom simulations, greatly constraining their use. Here, we propose a high-throughput sequence-based method for predicting extant fold switchers that transition from -helix in one conformation to {beta}-strand in the other. This method leverages two previous observations: (1) -helix <-> {beta}-strand prediction discrepancies from JPred4 are a robust predictor of fold switching, and (2) the fold-switching regions (FSRs) of some extant fold switchers have different secondary structure propensities when expressed in isolation (isolated FSRs) than when expressed within the context of their parent protein (contextualized FSRs). Combining these two observations, we ran JPred4 on the sequences of isolated and contextualized FSRs from 14 known extant fold switchers and found -helix <->{beta}-strand prediction discrepancies in every case. To test the overall robustness of this finding, we randomly selected regions of proteins not expected to switch folds (single-fold proteins) and found significantly fewer -helix <-> {beta}-strand prediction discrepancies (p < 4.2*10-20, Kolmogorov-Smirnov test). Combining these discrepancies with the overall percentage of predicted secondary structure, we developed a classifier that often robustly identifies extant fold switchers (Matthews Correlation Coefficient of 0.70). Although this classifier had a high false negative rate (6/14), its false positive rate was very low (1/211), suggesting that it can be used to predict a subset of extant fold switchers from billions of available genomic sequences.

bioinformatics↗